package com.atguigu.day12;

import com.atguigu.bean.WaterSensor;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.functions.AggregateFunction;
import org.apache.flink.table.functions.TableAggregateFunction;
import org.apache.flink.util.Collector;

import static org.apache.flink.table.api.Expressions.$;
import static org.apache.flink.table.api.Expressions.call;

public class Flink09_SQL_UDF_UDTAFun {
    public static void main(String[] args) {
        //1.获取流的执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        env.setParallelism(1);

        //2.获取表的执行环境
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

        //3.从端口读取数据并转为WaterSensor
        SingleOutputStreamOperator<WaterSensor> streamSource = env.socketTextStream("localhost", 9999)
                .map(new MapFunction<String, WaterSensor>() {
                    @Override
                    public WaterSensor map(String value) throws Exception {
                        String[] split = value.split(",");
                        return new WaterSensor(split[0], Long.parseLong(split[1]), Integer.parseInt(split[2]));
                    }
                });

        //4.将流转为表
        Table table = tableEnv.fromDataStream(streamSource);

        tableEnv.createTemporaryView("sensor",table);

        //不注册直接使用（只能在TableAPI中使用）
/*        table.groupBy($("id"))
                .flatAggregate(call(MyUDTAF.class,$("vc")).as("topVc","rank"))
                .select($("id"),$("topVc"),$("rank"))
                .execute()
                .print();*/

        //先注册再使用
        tableEnv.createTemporarySystemFunction("myTop2",MyUDTAF.class);
               table.groupBy($("id"))
                .flatAggregate(call("myTop2",$("vc")))
                .select($("id"),$("f0"),$("f1"))
                .execute()
                .print();

    }

    public static class MyTopAcc{
        //第一名的水位值
        public Integer first;
        //第二名的水位值
        public Integer second;
    }

    //TODO 自定义一个表聚合函数（多进多出） 实现Top2的功能
    public static class MyUDTAF extends TableAggregateFunction<Tuple2<Integer,String>,MyTopAcc>{

        @Override
        public MyTopAcc createAccumulator() {
            MyTopAcc myTopAcc = new MyTopAcc();
            myTopAcc.first = Integer.MIN_VALUE;
            myTopAcc.second = Integer.MIN_VALUE;
            return myTopAcc;
        }

        public void accumulate(MyTopAcc acc, Integer value) {
            //判断当前数据是否大于第一名的值
            if (acc.first<value){
                //之前的第一名是第二名
                acc.second = acc.first;

                //当前这个值是第一名
                acc.first = value;
            } else if (acc.second < value) {
                acc.second = value;
            }
        }

        public void emitValue(MyTopAcc acc, Collector<Tuple2<Integer,String>> out){
            //如果有第一名的话再将第一名发送出去
            if (acc.first!=Integer.MIN_VALUE){
                out.collect(Tuple2.of(acc.first, "1"));
            }
            //如果有第二名的话再将第二名发送出去
            if (acc.second!=Integer.MIN_VALUE){
                out.collect(Tuple2.of(acc.second,"2"));

            }
        }
    }

}
